High-Performance Cluster Computing. Volume 1: Architecutes and Systems. Volume 2: Programming and Applications

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C. P. Ravikumar

Abstract

Edited by: Rajkumar Buyya
Prentice Hall PTR, Upper Saddle River, NJ, 1999
Volume 1: 881pp, ISBN 0-13-013784-7, $54.00
Volume 2: 700pp, ISBN 0-13-013786-5, $54.00

I used the two books as part of a course that I taught at IIT Delhi during July-Dec 1999. The course was called Special Topics in Computers and included Masters students from the Departments of Electrical Engineering and Computer Science. The idea behind the course was to introduce elements of Distributed and Clustered Computing to students who already have some background in Computer Architecture. In my opinion, a single course in Computer Architecture at the Masters level cannot do justice to the developments that have taken place in this exciting field over the past decades. I have been teaching Computer Architecture at IIT Delhi for about 8 years now and find that the number of topics that I have to include in the course has been increasing very quickly over the years! In 1992, when I first taught the course, I used to teach about Pipelined Computers, Systolic Arrays, SIMD array processors, and Multiprocessors. As time has passed, it has become necessary to include topics such as high-performance interconnection networks, wormhole routing, cache coherence protocols, instruction pipelines, superscalar processors, and instruction-level parallelism. More recently, I have realized that it is also necessary to teach elements of distributed computing and clustered computing. I believe that a course on selected topics from distributed and clustered computing is essential to all branches of Engineering today. High-performance computing is essential to all branches of Engineering, and high-performance clustered computing on clusters of workstations/PCs makes a lot of economical sense.

A course such as this is interesting because it is easy for the students to practice what is taught in such a class without too many infrastructures. This makes the course very exciting to students. When I taught parallel algorithms in my class, I could not ask my students to develop these algorithms for lack of good infrastructure. However, a cluster of workstations and PCs is available in almost every University today. Distributed computing is highly popular with students. Students are eager to learn Java and network programming.

Rajkumar Buyya's edited volumes have arrived at the right time to provide the right kind of teaching material for the type of course, which I have above mentioned. The first volume covers architectural and system-level issues of clustered computing systems. It has 36 chapters organized into four sections, spanning 811 pages. Section I develops the motivation for high-performance clustered computing. Section II introduces various networking protocols and I/O mechanisms that are useful in clustered computing. Section III covers OS issues such as process scheduling and load balancing. Section IV includes a number of case studies of existing systems. The editor has made a considerable effort in gathering learning material for the volume. I think that this volume could be an excellent text for an advanced course on Computer Architecture. In the course that I taught, I used parts of Section I and IV. To me, the second volume proved more useful.

The second volume concerns with applications of clustered computing and applications programming. It is divided into 3 sections. There are 29 chapters that span 604 pages. Both volumes have carefully prepared Glossaries and Indexes. The first section of the second volume is on various programming environments and development tools. Although I limited myself to the discussion of the Parallel Virtual Machine (PVM) and Message Passing Interface (MPI), the editor has also included entire chapters on linking of these two environments, active objects, component-based approach, LiPS, and WebOS. There is a chapter of debugging parallelized code that can be highly valuable for students and developers of applications. The second section is on Java for high-performance computing. These topics raised a lot of interest among students when I taught the course. The third section is on specific algorithms and applications such as parallel genetic algorithms, parallel simulation, distributed database systems, graphics and image processing. The authors who have contributed to the two volumes are all known experts in the areas of Computer Architecture, Computer Networks, Distributed Computing, and Operating Systems. The authors and the editor must be congratulated on this extraordinary effort to compile so much useful material under one place. The books can not only serve as reference material to professional programmers in the modern IT industry, it can also serve as excellent teaching material for courses related to Computer Architecture, Distributed Computing, and Operating Systems. The web page that the editor has created for the book is also a wonderful repository of learning material available on the web. I recommend these volumes wholeheartedly to all serious researchers and students interested in the areas of high-performance computing in general and clustered computing in particular.

C. P. Ravikumar,
IIT Delhi

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